Adaptive filtering for more reliably determining physiological parameters

ABSTRACT

Apparatus for reducing an interference portion in a time-discrete signal further including a useful portion, including a first provider for providing the time-discrete signal including the interference portion and the useful portion; a second provider for providing a first time-discrete reference signal including a first interference portion, and a second time-discrete reference signal including a second interference portion, the second interference portion being shifted in phase relative to the first interference portion. The apparatus further includes a subtractor for generating a differential signal from the two reference signals, the differential signal including a frequency component caused by the first and second interference portions; and a manipulator for manipulating the time-discrete signal on the basis of the differential signal such that in a manipulated time-discrete signal the frequency component is reduced.

BACKGROUND OF THE INVENTION

The present invention relates to an apparatus for reducing aninterference portion in a time-discrete signal for more reliablydetermining a physiological parameter from the time-discrete signal. Themethod may be applied in plethysmogram-based measuring methods (e.g.plethysmography, pulse oximetry) for the purpose of suppressing aliasinginterferences.

Plethysmography is an optical method of obtaining a so-calledplethysmogram which provides information about the pulse frequency andthe oxygen saturation of the blood of a subject. A plethysmogram is agraphic illustration of volume changes. In this field of application, itis specifically the volume changes of an arterial blood flow at alocalized measurement site of the human body which are detected as theplethysmogram. To implement this in technical terms, light is radiatedthrough tissue at a body location having arterial blood vessels. Thepatient has a sensor applied to him/her which contains a light sourceand a photoreceiver, so that the light passes through the tissue layer,and so that the remaining light intensity impinges upon thephotoreceiver. Within the body, the light undergoes an attenuation whichis dependent, among other things, on the wavelength of the light source,the type and concentration of the substances in the irradiated tissue,and on the pulsation of the blood. The signal of the photoreceiver whichhas thus been obtained is present in the form of a photocurrent, isdependent on the above-mentioned general conditions, and corresponds, ina first approximation, to the changes in the blood volume of arterialvessels which are caused by contraction of the heart muscle. FIG. 24shows the basic architecture of an apparatus for detecting aplethysmogram. A microcontroller (μC) controls, via two driver stages,two LEDs of different wavelengths, one light source being sufficient, inprinciple, for creating a plethysmogram. The LEDs depicted in FIG. 24emit light in the red and infrared regions. The light emitted by theLEDs subsequently passes through the tissue of the subject, in FIG. 24this is depicted, by way of example, as a finger. Once the light haspassed through the tissue of the subject, it will impinge upon aphotosensor. The photosensor converts the optical signals intoelectrical signals and passes them on to processing electronics whichamplify the signal, convert them from analog to digital and feed them tothe microcontroller (μC). The microcontroller (μC) then determines twoplethysmograms, one plethysmogram for each wavelength, from the digitalsignals fed to it. From the waveforms of the plethysmograms thusmeasured, physiological parameters, such as the heart rate or the oxygensaturation of the subject's blood, may be measured, with one singleplethysmogram being sufficient, in principle, for determining the heartrate, for determining the oxygen saturation of the blood, twoplethysmograms of light sources of different wavelengths being useful.

Pulse oximetry is a non-invasive method of measuring the oxygensaturation of the blood (SpO₂) and the heart rate (HR) by means of anoptical sensor. The oxygen saturation detected by the pulse oximeter isspecifically referred to as the SpO₂ value. The oxygen saturation isdefined as the ratio of the concentration of oxygen-saturated hemoglobinmolecules and the overall hemoglobin concentration, and is indicated inpercent. A component of the pulse oximeter is a sensor having twointegrated light sources and being configured similar to aplethysmograph, cf. FIG. 24. In pulse oximetry, use is made of at leasttwo plethysmograms to determine the color of the arterial blood. Thecolor of the blood, in turn, is dependent on the oxygen saturation. Byselecting the wavelengths of the light sources well, it may be shownthat a quantity correlating well with the oxygen saturation may beobtained from the ratios of prominent points within the plethysmogram.Typically, the spectra of the receive signals of two light sources ofdifferent wavelengths are determined, and the quotient of specificspectral values is formed. This quotient will then be approximatelyproportional to the SpO₂ value of the blood.

An essential quality characteristic in comparing pulse oximeters is theresistance toward interferences. Filtering those unuseful signalportions which arise because of the movement of the patient isparticularly problematic. Even with small movements, the amplitudes ofthe motion artifacts may seem larger than those of the pulse wave withinthe signal. If the signal is highly overlaid by motion artifacts, thiswill lead to a temporary operational failure of the equipment, with thisproblem being signaled accordingly. In the worst case, the equipmentwill not detect the distorted measurement and will not issue a signal,so that the measurement values indicated will erroneously be held astrue. The quality of treatment of a patient may be clearly reduced dueto measurement values being incorrectly indicated. Especially in theenvironment of operating rooms, the above-mentioned distortionsrepresent a major disadvantage of pulse oximeters.

In addition to the motion artifacts, high-power light sources, such asthose of operating-room lamps, fluorescent lamps or monitors, may causeunwanted interferences in the signal. With conventional pulse oximetersor plethysmographs, this problem is typically diminished by introducingadditional measurement periods for determining the ambient light, and bysubsequently subtracting the ambient-light measurement from theuseful-signal measurement. During these measurement periods or timeslots, all light sources of the sensor are switched off, and only theambient light is measured. The ambient-light intensity is subtractedfrom the plethysmogram, and thus the portion of ambient light is largelyseparated from the pulse signal. However, especially with pulsating orAC-powered ambient-light sources, an interference portion will remainwithin the plethysmogram. The interference portion within theplethysmogram thus highly depends on the electronic equipment, orinterferers, used in the surroundings. Especially in the intensive careof patients, a multitude of electronic devices and tools are employed,so that the susceptibility of pulse oximeters and plethysmographs tointerference is a given fact particularly in intensive-careenvironments. Particularly in the field of intensive care, however,measurement errors of physiological parameters such as the heart rate orthe blood oxygen saturation are extremely critical and may entailserious consequences.

In pulse oximetry, transmission and remission sensors have several LEDs(transmitters) and only one photodiode (receiver). The subject's tissueis irradiated by LEDs of different wavelengths, and the photodiodereceives the light of different wavelengths from the tissue. Inprinciple, it would be possible to differentiate various channels bymeans of the wavelengths of the LEDs, e.g. by color filters present atseveral photodiodes. Since this involves a large amount of technicalexpenditure on the side of the photodiode, the intensities of the LEDsmay be modulated. Only then is it possible to differentiate between thewavelengths by means of a single broad-band photodiode.

In order to enable the receiver to differentiate between varioustransmit sources (LEDs) having different wavelengths, TDMA concepts(time division multiple access) are employed with known pulse oximeters.Each sensor LED has a time window assigned to it within which it isswitched on. FIG. 25 illustrates this time sequence of signals. One mayrecognize that the various LEDs successively have time slots of equaldurations associated with them which are separated by dark periods ofequal durations. FIG. 25 shows a schematic sequence with three differentLEDs. The LEDs of different wavelengths successively light up for ashort time duration, in FIG. 25, the bright periods of the LEDs aredesignated by “LED 1”, “LED 2”, and “LED 3”. Typical frequencies withwhich the light sources of current pulse oximeters are controlled amountto 20-50 Hz. By adding additional dark phases during which none of theLEDs lights up, designated by “DARK” in FIG. 25, one tries to measurethe signal portion caused by ambient light, and to subsequently subtractit from the useful signal. Nevertheless, the results are often distortedby ambient light or by high-frequency surgery influences. Inhigh-frequency surgery, tissue is cut by means of high-frequencyvoltages. These high frequencies cause inductions in lines of the pulseoximeters and may thus interfere with their functioning. The localinfluences may be largely suppressed, since the sensors are protectedagainst irradiation from the outside. Nevertheless, ambient light willenter into the shell of the sensor.

The signal quality is clearly improved by subtracting the ambient-lightportion, determined by adding dark phases. However, interferenceartifacts will remain which may lead to incorrect SpO₂ values. Up tonow, it has not been possible, despite numerous attempts, to removethose interferences, which are caused by fluorescent lamps, infraredheat lamps, operating-room illumination and monitors, from the usefulsignal. Since in pulse oximeters and plethysmographs, the ratio betweenuseful signals, i.e. those signal portions caused by the change involume of the tissue, and the interferences may be very unfavorable,those interferences which are distorted further by signal processing arealso relevant. For example, prior to an analog/digital conversion,signals are low-pass filtered to avoid errors caused by subsampling.Since the filters used only ever have a finite attenuation within thestop band, errors caused by subsampling, also referred to aliasingerrors, will nevertheless arise. Depending on the original interferingfrequency, these interferences will then be mirrored into the usefulrange, where they may occur at different frequencies.

A further example of dynamic interferences may be found with subjectswho have long-term measurements conducted on them. They wear a sensorwith integrated LEDs and a photoreceiver over a relatively long timeperiod for detecting long-term data. These patients or subjects, forexample during car journeys through tree-lined streets or streets linedby many high buildings, are subject to pronounced and, as the case maybe, rapid changes in the lighting conditions. In places, these changinglighting conditions express themselves in a manner very similar to theinterferences in in-patient environments of hospitals. In principle,subjects subjected to long-term measurements are exposed to amultiplicity of ambient-light influences which may give rise to a wholespectrum of interferences.

The susceptibility of current pulse oximeters and plethysmographs tointerferences will rise if the above-mentioned interferers are locatedwithin their surroundings. Especially in operating rooms orintensive-care units, there are a multiplicity of electronic devices, orelectronic interferers. Particularly in such environments, thus, thesusceptibility of current pulse oximeters and plethysmographs tointerferences increases. This significant disadvantage may entailserious consequences for subjects if such situations give rise tomeasurement errors which cannot be immediately identified as such.

Known plethysmography methods may be found in the following documents,for example:

EP 1374764 A1/WO 2002054950 A08, which describes a basic circuit formeasuring and detecting a plethysmogram, and deals with theabove-described signal processing in detail.

EP 208201 A2/A3, wherein optical detection of a change of volume of abody part, and an evaluation device for evaluating the optical signalsare protected, in principle. The method described there makes use of thechanging outward volume change of extremities caused by the pulse andthe changes in blood pressure associated therewith.

EP 341059 A3. Here, a basic pulse oximetry method is described whichexploits light sources (LEDs) of different wavelengths. Light ofdifferent wavelengths is radiated through the subject's tissue, thelight signals are absorbed from the tissue by means of optical sensorsand are evaluated by a corresponding analog signal processing.

EP 314331 B1, a pulse oximetry method also based on light of differentwavelengths is used for radiating the tissue of a subject. The opticalsignals thus obtained are converted to electric signals, and a valuewhich provides insights into the oxygen saturation of the subject'sblood is extracted therefrom.

EP 1254628 A1, the pulse oximeter protected here is also configured todetermine oxygen saturation of blood, the method proposed hereadditionally reducing interferences caused by cross-talk.

U.S. Pat. No. 5,503,144/U.S. Pat. No. 6,714,803, here a description isgiven of signal processing methods for linear regression which determinean SpO₂ value by means of two plethysmograms. A correlation coefficientwhich serves as the reliability measure is determined from among the twoplethysmograms.

DE 692 29 994 T2 discloses a signal processor taking up a first signaland a second signal correlated with the first signal. Both signals eachhave a useful signal portion and an unuseful signal portion. The signalsmay be taken up by the spreading of energy through a medium and bymeasuring an attenuated signal after transmission or reflection.Alternatively, the signals may be taken up by measuring energy createdby the medium.

The first and second signals measured are processed so as to take up anoise reference signal which does not include the useful signal portionsof the respective first and second signals measured. The remainingunuseful signal portions of the first and second signals measured arecombined to shape a noise reference signal. This noise reference signalis correlated with each of the unuseful signal portions of the first andsecond signals measured.

The noise signal is then used to remove the unuseful signal portionswithin the first and second signals measured by means of an adaptivenoise eliminating means. An adaptive noise eliminating means may be seenanalogously to a dynamic multiband-stop filter which dynamically changesits transfer function in response to a noise reference signal and to thesignal measured so as to eliminate frequencies from the signals measuredwhich are also present in the noise reference signal. A typical adaptivenoise eliminating means thus obtains the signal from which noise is tobe eliminated, and a noise reference signal. The output of the adaptivenoise eliminating means then is the useful signal with reduced noise.

US 2005/0187451 describes a method of use in a signal attenuationmeasurement for determining a physiological parameter of a patient.Further, a description is given of an apparatus for determining aphysiological parameter of a patient from at least two signals whichpassed tissue of the patient and were attenuated there. In this context,the two signals are multiplexed using an FOCDM method (FOCDM=frequencyorthogonal code division multiplex). The method enables separation ofthe two signals and suppression of external interference.

SUMMARY

According to an embodiment, an apparatus for reducing an interferenceportion in a time-discrete signal further including a useful portion mayhave: a first provider for providing the time-discrete signal includingthe interference portion and the useful portion, the first providerbeing adapted to sample an iterative optical signal which corresponds tobright periods during which a transmit light source adopts an on state;a second provider for providing a first time-discrete reference signalincluding a first frequency component of the interference portion, and asecond time-discrete signal including a second frequency component ofthe interference portion, the first and second frequency componentsbeing shifted in phase, and the second provider for providing the firstand second reference signals being adapted to sample two optical signalswhich correspond to dark periods during which no transmit light sourceadopts an on state; a subtractor for generating a differential signalfrom the two reference signals, the differential signal including athird frequency component caused by the first and second frequencycomponents; and a manipulator for manipulating the time-discrete signalon the basis of the differential signal, such that in a manipulatedtime-discrete signal the interference portion is reduced.

According to another embodiment, a method of reducing an interferenceportion in a time-discrete signal further including a useful portion mayhave the steps of: providing a time-discrete signal including theinterference portion and the useful portion, including sampling aniterative optical signal which corresponds to bright periods duringwhich a transmit light source adopts an on state; providing a firsttime-discrete reference signal including a first frequency component ofthe interference portion; providing a second time-discrete referencesignal including a second frequency component of the interferenceportion, the first and second frequency components being shifted inphase, and providing the first and second reference signals includingsampling optical signals which correspond to dark periods during whichno transmit light source adopts an on state; subtracting the tworeference signals and providing a differential signal including a thirdfrequency component caused by the first and second frequency components;and manipulating the time-discrete signal on the basis of thedifferential signal such that in a manipulated time-discrete signal theinterference portion is reduced.

This object is achieved by an apparatus for reducing an interferenceportion in a time-discrete signal further including a useful portion,the apparatus comprising a first means for providing the time-discretesignal including the interference portion and the useful portion. Theapparatus further comprises a second means for providing a firsttime-discrete reference signal including a first interference portion,and a second time-discrete reference signal including a secondinterference portion, the second interference portion being shifted inphase relative to the first interference portion. The apparatus furthercomprises a subtraction means for generating a differential signal fromthe two reference signals, the differential signal including a frequencycomponent caused by the first and second interference portions, and ameans for manipulating the time-discrete signal, on the basis of thedifferential signal, such that in a manipulated signal the frequencycomponent is reduced.

In addition, the object is achieved by a method of reducing aninterference portion in a time-discrete signal further including auseful portion, by providing the time-discrete signal including theuseful portion and the interference portion, by providing a firsttime-discrete reference signal including a first interference portion,and by providing a second reference signal including a secondinterference portion, the second interference portion being shifted inphase relative to the first interference portion. In addition, theobject is achieved by subtracting the two reference signals andproviding a differential signal including a frequency component causedby the first and second interference portions, and by manipulating thetime-discrete signal, on the basis of the differential signal, such thatin a manipulated time-discrete signal the frequency component isreduced.

The core idea of the present invention is to reduce the interferenceportions which overlay the useful signal in plethysmography and pulseoximetry, in addition to subtraction of an ambient light measurement, byadaptive filtering. In pulse oximetry or plethysmography, interferencescaused by sub-sampling (aliasing) occur in addition to the interferencescaused by ambient light. The former interferences are mirrored fromhigher frequency ranges into the useful band and are shifted in phase inthe individual channels due to the sub-sampling. By formation of adifferential signal from the channels of the dark phases, a signal maybe extracted which contains only those interferences which are caused bysub-sampling. On the basis of the interference portions in this signal,the interference portions in the bright phase channels may also bereduced.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the present invention will be detailed subsequentlyreferring to the appended drawings, in which:

FIG. 1 a) is a schematic representation of an inventive embodiment

FIG. 1 b) is a schematic representation of an inventive embodiment

FIG. 2 a) is a schematic representation of the irregular arrangement ofthe bright periods

FIG. 2 b) shows a regular arrangement of the bright periods inaccordance with conventional pulse oximeters

FIG. 3 is block diagram of an implementation of the embodiment

FIG. 4 is a schematized representation of a spectrum of a signal withinthe baseband

FIG. 5 is a schematized representation of a spectrum of a signal withinthe transmission band

FIG. 6 is a schematic representation of two orthogonal chip sequences ofa length of 101 chips

FIG. 7 is a schematic representation of a spectrum of a chip sequence ofa length of 101 chips

FIG. 8 is a schematic representation of the signal within thetransmission band

FIG. 9 is a schematic representation of the spread interference andde-spreading within the frequency range

FIG. 9 a) is a schematic representation of the spectrum within thebaseband

FIG. 9 b) is a schematic representation of the spectrum of the chipsequence

FIG. 9 c) is a schematic representation of the spectrum within thetransmission band

FIG. 9 d) is a schematic representation of the spectrum of the usefulportions and interference portions within the baseband afterde-spreading

FIG. 10 shows two exemplary received waveforms of two LEDs havingdifferent wavelengths

FIG. 11 is a representation of two exemplary waveforms for the darkduration and the ambient-light measurement, respectively

FIG. 12 depicts an exemplary transmission function of an extractionfilter with an attenuation of 15 dB and a suppression of 100 Hz;enlargement in the area of 100 Hz

FIG. 13 depicts exemplary waveforms of the bright transmit channels fromwhich the ambient-light signal has been subtracted, the enlargementshows the reference signal

FIG. 14 is a schematic representation of the block formation for furthersignal processing, l_(B) corresponds to the block length, l_(a) is ameasure of the overlap

FIG. 15 a) shows an exemplary waveform of an input signal and of thelow-pass filtered DC signal (DC portion)

FIG. 15 b) shows an exemplary waveform of the high-pass filtered signal(AC portion)

FIG. 16 depicts a model of the adaptive filter, with the inputquantities on the left and the output quantities on the right, thereference signal being designated by W^(A) _(c)

FIG. 17 depicts an exemplary curve of a Kaiser-Bessel window having ablock length of 256 points

FIG. 18 is an exemplary spectral curve of the normalized useful signalsfor the two bright transmit channels, red and infrared

FIG. 19 is an exemplary representation of the two spectra for red andinfrared transmit channels, spectral values of identical frequenciesbeing plotted against one another

FIG. 20 a) is a schematic representation of the least squares fit methodfor minimizing a vertical distance from a straight line

FIG. 20 b) is a schematic representation of the total least squares fitmethod for minimizing the actual distances from a straight line

FIG. 21 a) depicts an exemplary curve of the quotient between the redtransmit channel and the infrared transmit channel at four differentpoints in time k2

FIG. 21 b) shows an exemplary curve of a reference spectrum determinedusing the method of the complex total least squares fit method

FIG. 22 depicts an exemplary spectrum of a waveform, wherein theamplitudes of the interference are larger than the amplitudes of thepulse wave

FIG. 23 depicts an exemplary characteristic curve of a calibrationfunction

FIG. 24 shows a basic block diagram of the hardware of a conventionalpulse oximeter; and

FIG. 25 is a schematized representation of a time division multipleaccess method (TDMA).

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 a) shows a schematized representation of an inventive embodimentcomprising an apparatus 100 for reducing an interference portion. Afirst means 110 for providing a time-discrete signal representing, forexample, a disturbed signal of a plethysmograph. This signal may havecome into being, for example, by radiating a tissue of a subject withinfrared light. In addition, FIG. 1 a) shows a second means 120 forproviding first and second reference signals representing, for example,two dark phase channels of a plethysmograph. These two channelsinitially contain interferences caused by influences of ambient light inthe useful range, as well as interferences caused by sub-sampling. Sincethe interferences located within the useful range are in the same phasein the two reference channels, they may be masked out by formation ofthe differential signal. This is achieved by a subtraction means 130 forgenerating a differential signal from the reference signals. Thedifferential signal is supplied to a means 140 for manipulating thetime-discrete signal. The means 140 for manipulating obtains thetime-discrete signal from the means 110 for providing the time-discretesignal, and manipulates it on the basis of the differential signal.

In a further embodiment, as is shown in FIG. 1 b), the apparatus 100further comprises, in addition to the means already shown in FIG. 1 a),a means 150 for forming a weighted sum from the two reference signals,which is then supplied to the first means 110 for providing thetime-discrete signal so as to reduce in-phase interferences in thetime-discrete signal. In addition, the time-discrete signal manipulatedby the means 140 for manipulating is supplied to a processing means 160,where the signal is processed further, for example a physiologicalparameter is extracted here.

In an inventive embodiment, a light source whose light is coupled into apart of a subject's body, and the signal received by a photodetector, iscontrolled such that it adopts, in a iterating sequence, the on state atirregular intervals. The irregularity causes an expansion to occurwithin the spectral range of the signal. The additional spectralcomponents of the light signal give rise to additional interferenceimmunity. In the simplest case, two spectral lines of the same levelwill arise. Since the probability that both spectral components will beinterfered with at the same time is smaller than the probability that asingle spectral component will be interfered with, a diversity gainarises in the frequency range. This diversity gain may be implemented bycorresponding signal processing, so that increased interference immunityand, thus, increased reliability of the measurement of a physiologicalparameter is achieved by the irregular control of the light sources. Inaddition, a so-called spread gain results. By the irregular controlling,the energy of the useful signal is evenly distributed to severalfrequency portions. Since the irregularity is known, these energyportions may again be coherently overlaid within the receiver.Interference portions having the same frequencies are also overlaidwithin the receiver; however, since same are interdependent, a coherentoverlay takes place here, so that a gain results for the useful signal.A narrow-band interferer which overlays the useful signal only at onefrequency portion will experience, within the receiver, a spectralexpansion which is analogous to that of the useful signal within thetransmitter, since in both cases, signal portions are combined atirregular points in time.

This irregularity of the bright periods is depicted in FIG. 2 a in aschematized manner. FIG. 2 a shows an iterating sequence of a durationof ΔT. Within one sequence, a light source H₁ adopts an on state twice.This is indicated in FIG. 2 a by the entries H₁. During the othermoments, when no entries are present within the time raster in FIG. 2 a,the light source is switched off. For comparison, FIG. 2 b depicts asequence of a conventional pulse oximeter. FIG. 2 b shows a timedivision multiple access method (TDMA), wherein two light sources arecontrolled. During one sequence, each light source adopts the on statefor one time slot. This is indicated by H₁ and H₂ in FIG. 2 b. Duringthe other time periods, depicted by D₁ and D₂ in FIG. 2 b (D represents“DARK”), none of the two light sourced is to have adopted an on state.

Irregular controlling at the light source corresponds to a spreadspectrum modulation. In combination with an inventive adaptive filteringconnected downstream, the spread spectrum modulation reduces signalsportions which are to be attributed to ambient-light influences orelectromagnetic interfering sources (e.g. high-frequency surgery), andsuch signal portions which are to be attributed to the subsampling. Inaddition, subsequent signal processing also enables a particularlyefficient measurement of the oxygen saturation in the blood and of theheart rate of a patient, it also being possible with the present methodto perform reliable measurements even with a low arterial blood volumepulsation and while the patient is moving. The increased reliability ofthe measurement thus directly causes an increase in the quality oftreatment for a patient. Thus, one advantage of the present invention isthe fact that due to the increased reliability of the measurement valuesof a pulse oximeter, in particular in critical environments such asoperating rooms or intensive-care units, increased chances of recoveryand more efficient methods of treatment are enabled.

FIG. 3 shows an implementation of the embodiment. In FIG. 3, a spreadspectrum modulation 300 is initially converted to an optical signal byan LED driver stage 305. In accordance with the spread spectrummodulation received, the LED driver means 305 couples light signals intoa tissue 310 (e.g. into a finger), whereupon the light signals aremodulated on their way through the tissue, and are subsequently receivedby a photoreceiver 315. Photoreceiver 315 converts the optical signalsreceived to electrical signals and feeds same to an analog/digitalconversion means 320 which converts the analog signal to a digitalsignal. The analog/digital conversion means 320 has a spread spectrumdemodulator 325 connected downstream from it.

After the spread spectrum demodulation 325, the signal is adaptivelyfiltered 330 in accordance with the invention and thereafter subject toa Fourier transformation 335. In a next step, a spectral mask 340 is nowapplied to the spectrum of the signal, whereupon the heart rate of thesubject may be established and will then be output at an output 345. Ina next analysis step, the so-called “complex total least squares fit”method 350, a variance of the difference of the different spectra whichhave been measured for light having different wavelengths may bedetermined, via a statistical analysis in the frequency range, and beoutput at the output 355 as a measure of reliability. Using the initialvalue provided by the “complex total least squares fit” means 350, anassociated blood saturation value (SpO₂ value) may now be output, via acalibration function 360, at the output 365.

In order to be able to measure the light absorption of the tissue 310with several light sources 305 having different wavelengths, and bymeans of a broad-band photoreceiver 315, a modulation method may beused, consisting of modulator 300 and demodulator 325. To bettersuppress interferences, the spread spectrum method is employed. Thismodulation method is based on the fact that because of the irregularityof the bright periods, the spectrum of the baseband signal is spread, orexpanded. This effect is illustrated by FIGS. 4 to 9. Initially, FIG. 4shows a spectrum |I(f)| of a baseband signal, the cutoff frequency ofwhich is referred to as f_(B). With conventional modulation methods,such as amplitude modulation, the spectrum of the baseband signal isshifted into a frequency range more suitable for the transmission. FIG.5 illustrates this case, and depicts the shifted spectrum |I_(A)(f)|.Such a spectrum results when the baseband signal is multiplied by ahigher carrier frequency. The spectrum of the baseband signal remainsunchanged in terms of its shape and energy. If this signal is overlaidby an interferer, it will not be possible to suppress this interferenceby demodulation, i.e. by means of a shift-back from the transmissionband into the baseband. In the case of the spread spectrum modulation asis employed according to the invention, each transmit channel, which isunderstood to mean the transmit light signals of a wavelength, has aso-called chip sequence associated therewith which has beenpre-computed. A chip sequence consists of a finite sequence of ones andzeros which are typically clocked in a frequency which is a hundredtimes higher than, by comparison, in a TDMA concept. The clock frequencyis about 3 kHz. From a mathematical point of view, the chip sequencesmay meet certain characteristics in order to achieve the desiredspreading action of the interfering signal, and to enable thereconstruction of the plethysmograms as well as of the ambient-lightchannels. In principle, the chip sequences may be orthogonal to be ableto implement a channel separation in the demodulation, and so that ademodulation without any cross-talk is enabled.

FIG. 6 shows a schematic representation of two orthogonal chipsequences, the length of a chip sequence equaling 101 chips in theembodiment contemplated here. FIG. 6 depicts a time beam of a durationof 101 chip durations. The values of second chip sequences c(k) areplotted over these 101 chip durations. In the diagram, the two chipsequences are differentiated by dotted and solid lines, respectively.Whenever a chip sequence adopts a value of 1, this means that the lightsource associated is placed into the on state. It may be clearly seen inFIG. 6 that the two chip sequences are orthogonal, i.e. that the twoassociated light sources will never adopt the on state at the same time.In principle, it is also possible to employ chip sequences whichsimultaneously result in a 1, or it is possible to employ othersequences having other properties. However, particular emphasis shall beplaced on the property of the sequences which causes the individualbright periods to occur at irregular intervals, so that a spectralspread is achieved. In addition, it may be clearly seen in FIG. 6 thatthe individual bright periods within a sequence are arranged in anirregular manner, and that there are points in time when both chipsequences take on the value of 0, i.e. when both light sources areswitched off in the implementation.

A further important property of the chip sequences is that theirspectrum should be spread as evenly as possible, so that the signalenergy will spread as evenly as possible to a frequency range as broadas possible.

FIG. 7 shows the spectrum, i.e. the frequency range, of one of the chipsequences depicted in FIG. 6. It may be clearly seen in FIG. 7 that thespectrum of such a sequence is evenly spread, i.e. the spectrum iscomposed of equidistant identical values. The high direct componentrepresented by the excessive value at the frequency of 0, may beexplained in that the chip sequence can only adopt the values of 0and 1. Thus, the sequence is not free from a mean value.

The spectrum of a chip sequence may therefore be regarded as a “comb” ofequidistant carriers of identical amplitudes. The spectral equipartitionof a chip sequence results in that a narrow-band interferer will bespread, after demodulation, into a broad-band noise. In theimplementation of the advantageous embodiment is depicted in FIG. 3, thetwo LEDs are controlled using the chip sequences depicted in FIG. 6.

FIG. 8 shows the schematic representation of the signal of FIG. 4 withinthe transmission band |I_(c)(f)|. The baseband signal, as is depicted inFIG. 4, maintains its spectral shape, but its energy is distributed tomany frequencies. This process is also referred to as spreading. If thesignal depicted in FIG. 8 is interfered with by a narrow-bandinterferer, said interferer will be subject to spreading in thedemodulation, whereas the energy portions of the signal of FIG. 8 willagain overlay one another in a coherent manner within the baseband.Here, the demodulation corresponds to a renewed multiplication by therespective chip sequence. The result of the multiplication is thensummed up across a length of chip sequences. Thus, if a receive signalis multiplied by one of the chip sequences, as are depicted in FIG. 6,it may easily be seen from FIG. 6 that by the multiplication, only thosereceive signals values are masked out from the receive signal which arereceived at a moment which correspond to a one in the respective chipsequence. These individual signal portions are then summed up across achip sequence, as a result of which they will coherently, i.e.constructively, overlay one another. An interfering signal which hasoverlaid the receive signal is also masked in only at the respectivemoments in time. Also, the interfering signals are sampled at therespective moments in time and are summed up across the length of chipsequence. However, the interfering signals do not coherently overlay oneanother at the sampling moments, so that they will actually experience aspreading across the de-spreading, i.e. the multiplication by the chipsequence, so that after demodulation, these signals will be present inan attenuated form only.

FIGS. 9 a)-d) depict the operation of the spreading once again withinthe frequency range. FIG. 9 a) shows the spectrum of a signal within thebaseband. FIG. 9 b) shows the spectrum of a chip sequence, the spectrumideally being evenly distributed in spectral terms. FIG. 9 c) shows thespread baseband signal which now has energy portions at each individualfrequency of the chip sequence. The energy of the baseband signal hasbeen spread to the frequencies contained within the chip sequence. Inthe inventive implementation, the signal is received in this form fromthe tissue by the photosensor, the actual useful signal then wasmodulated to the spread signal through the tissue. FIG. 9 c) furtherdepicts two interferences, “interference 1” and “interference 2”. Thetwo interferences are narrow-band interferers as may be caused, e.g., byfluorescent lamps or high-frequency scalpels. FIG. 9 d) shows thespectrum of the signal after demodulation, or after de-spreading. It maybe seen that the baseband signal has been reconstructed, and thatadditional frequencies of the interfering signals within the basebandhave been added. FIG. 9 d) also shows that the remaining frequencies ofthe interference have clearly smaller amplitudes than the originalinterference itself, which is due to the spreading of the interferingsignal.

Legendre sequences are chip sequences which meet the characteristicsuseful here and which exhibit good auto and cross-correlationcharacteristics. In the contemplated implementation of the embodiment,the sequences modulate two bright transmit channels and two darktransmit channels. The spectral properties of all sequences areidentical and meet the equidistribution useful within the spectralrange. In addition, a total of four sequences are considered, the foursequences being orthogonal to one another, which means that no twosequences will adopt the value of 1 at the same time. In principle, theuse of other sequences is also feasible, the irregularity property ofthe bright periods is to be emphasized here, this does not presupposethat at any moment in time, only one sequence may have a bright period.Two of the four sequences are used in an implementation of theembodiment to control two LEDs having different wavelengths (red andinfrared), the two remaining sequences serve to modulate ambient-lightchannels, they correspond to dark channels.

The LEDs are now controlled as monochromatic light sources via LEDdriver 305 of FIG. 3. The light of the LEDs which is modulated with thechip sequences passes through a tissue layer, and depending on thewavelength of the light source, it experiences an adequate attenuationin the process. The radiation of the LEDs, which is attenuated by thetissue, impinges at photoreceiver 315, is converted to a proportionalphotocurrent there, and is subsequently sampled, using an analog/digitalconverter 320, in a manner which is synchronous to the clock ofmodulator 300. The synchronicity between the modulator within thetransmitter, and the AD converter and/or demodulator within the receivermay optionally be achieved by a control means which dictates clocks toboth the transmitter and the receiver via control leads. The signalwhich has been synchronously sampled is fed to the spread spectrumdemodulator 325. By means of the demodulation, spread spectrumdemodulator 325 divides the signal of the photoreceiver up intoindividual channels. In a practically oriented implementation, these aretwo pulse channels for red and infrared LEDs, as well as two channelsfor measuring the ambient light. FIG. 10 shows two exemplary waveforms,the lower one corresponding to the red LED, and the upper one to theinfrared LED. It may be seen in FIG. 10 that both signals are overlaidby a higher-frequency signal portion originating from the pulse signalof the subject, that both signals have a high direct component, and thatboth signals have a low-frequency pulsatile portion which may have beencaused, for example, by changes in ambient light due to movements on thepart of the subject.

FIG. 11 shows two exemplary waveforms for the two dark channels. Inthese two signals, too, it is possible to recognize the high-frequencyportion originating from the pulse signal of the subject, as well as aninterfering portion to be attributed to ambient-light changes. Thedirect component in FIG. 11 is correspondingly smaller than the directcomponent in FIG. 10, since both light sources are switched off duringthe dark channel phases. In order to specifically calculate, andextract, the influences of the ambient light from the bright transmitchannels, the mean value of the two ambient-light channels is subtractedfrom the two bright transmit channels so as to remove that portion ofambient light which is below the two sampling frequencies from thesignal measured. The formation of the mean value corresponds to theinventive formation of a weighted sum, as is implemented, in accordancewith the invention, by a means 150 for forming a weighted sum in FIG. 1b).

For demodulation purposes, a so-called matched filter is used, for eachchip sequence, for extracting the transmit channels from the receivesignal. Such a matched filter is an implementation of the spreadspectrum modulator 325 of FIG. 3 and may be described as a mathematicaloperation with a chip sequence. The sensor signal is cyclicallymultiplied by the chip sequence, and the result is summed up over onechip-sequence length in each case. In the realization of the embodimentwhich is described here, these are the respective Legendre sequences.Mathematically speaking, the matched filter implements a scalar productbetween the chip sequence and the receive vector, i.e. the sampledreceive signal. Transmitter and receiver are synchronized. The scalarproduct leads to blockwise de-spreading of a transmit channel into thebaseband. What results at the same time is a subsampling with a factorwhich corresponds to the length of the chip sequence for the usefulsignal. To avoid aliasing, the bandwidth of the signal may be reducedprior to each subsampling operation. Thus, an anti-aliasing filter isuseful which may be integrated, along with the matched filter, into onefilter.

Studies have shown that interferences having large amplitudes are mainlydue to artificial illumination. In Europe, the mains frequency is 50 Hz,the fundamental wave of the power (or of the intensity) is therefore 100Hz, and its harmonic waves correspondingly amount to multiples of 100Hz. Depending on the intensity of the interference, the attenuation ofthe extraction filter within the stop band is not sufficient. On thebasis of these findings, the frequencies corresponding to a multiple of100 Hz may be suppressed by adjusting the properties of the extractionfilter (combined filter).

By way of example, FIG. 12 shows a transmission function of anextraction filter with an attenuation of 15 dB, wherein, additionally,the interferers are suppressed at multiples of 100 Hz. Thus, theextraction filter already includes a low-pass filter useful forsubsampling, and at the same time a matched filter for de-spreading thespread signal from the transmission band into the baseband. A filterwhich implements subsampling is also referred to as a subsampler, thematched filter for de-spreading the spread signal is also referred to asa correlator, since it correlates a predefined chip sequence with thereceive signal.

After extraction from the receive signal, the extracted and subsampledsignals are present. The degree of subsampling is dependent on thelength of the chip sequence. A sample of the useful signal results foreach chip-sequence length due to the matched filter. By using severalorthogonal chip sequences, several channels result during achip-sequence duration, in the inventive embodiment, there are fourchannels, two bright transmit channels of the red and infrared LEDs, aswell as two dark transmit channels, during which none of the transmitlight sources adopts an on state, and which are used for ambient-lightand interference compensation.

In addition, the interferences present above the useful band, i.e.interferences present above half the sampling frequency, are mirroredinto the useful band at 15 dB by the extraction filter. The attenuationof the interferences above half the sampling frequency depends on thechip-sequence length. In the inventive realization of the embodiment, achip-sequence length of 101 chips has been selected, which leads to anattenuation of 15 dB for interferences above half the samplingfrequency. At the same time, the filter implements additionalattenuation of all frequencies comprising a multiple of 100 Hz. FIG. 12shows an exemplary transmission function of an extraction filter.

After the extraction filter, the useful signals are present within thebaseband. To reduce the influence of the ambient light, in accordancewith the invention, the ambient-light portion is subtracted from theuseful signal, in accordance with the first means 110 for providing thetime-discrete signal in FIG. 1 b). In addition, a differential signal isgenerated for the adaptive filter 330 in accordance with the secondmeans 120 for providing the first and second time-discrete referencesignals, and with subtracting means 130, as depicted in FIGS. 1 a) and 1b). For ambient-light subtraction, a mean value is initially formed fromthe dark channels, which is then subtracted from the bright transmitchannels. Depending on the type of chip sequences used, and/or dependingon the configuration of the spectra of the individual chip sequences, itmay be advantageous not to determine the exact mean value of the darkchannels, but to linearly weight the dark channels. In theimplementation of the inventive embodiment, Legendre sequences of thelength of 101 chips are used. This implementation results in an optimalweighting of the dark channels of from 47.5% to 52.5%.

For the purposes of further inventive signal processing, it is importantto differentiate between two frequency bands into which an interferermay be categorized. On the one hand, the band exists below half thesampling frequency, the useful band. On the other hand, the band existsabove this frequency, the transmission band. Frequency components whichare due to interference and are categorized into the useful band may beremoved from the two useful signals (bright transmit channels of the redand infrared LEDs) by means of dark-phase subtraction. The signals ofthese frequencies are equal both in phase and in amplitude, andtherefore do not appear in the difference of the two dark channels, thedifferential signal. An interferer within the useful band (or thebaseband) will thus continuously result in 0 for the differentialsignal. An interferer within the useful band could be a light sourcewhich is detected by the photosensor through the tissue, and theintensity of which is modulated with the changes in volume of thearterial blood. However, these portions are not to be filtered out fromthe useful signal, as they contain the information desired (thepulsatile portion).

By contrast, an interferer could be categorized into the transmissionband. In this case, the attenuation of the extraction filter will setin, which initially causes the interference to fall into the useful bandin an attenuated state. In the implementation of the embodiment, thisattenuation amounts to 15 dB. In addition, signals of these frequenciesare subject to a phase shift which is different for each channel. Thiseffect is to be attributed to the sequential sampling; although theorthogonal chip sequences are interlaced, cf. FIG. 6, they realize thesamples at different moments in time. For signals above half thesampling frequency, this leads to a phase shift of the subsampledsignals in the individual channels.

Thus, the difference between the two dark transmit channels (thedifferential signal) does not result in an extinction of these signals,but results in a signal, the frequency components of which contain themirrored frequencies of the interferer from the transmission band. Thissignal now serves as a differential signal for an inventive adaptivefilter 330, so as to reduce the remaining interferences from thetransmission band as well. The ambient-light subtraction thus removesthe interferences from the useful band, but also contains phase-shiftedinterfering portions from the transmission band. Once the interferencesfrom the transmission band have experienced attenuation by theextraction, portions of this interference are now re-fed to the usefulsignal by the ambient-light subtraction. Therefore, what results is notthe full attenuation for the interfering signals from the transmissionband, but a smaller value. In the implementation of the inventiveembodiment, the attenuation of the extraction filter initially amountsto 15 dB, but is reduced again by 3 dB by the ambient-light subtraction,so that a total attenuation of 12 dB results for interferers from thetransmission band. FIG. 13 shows two exemplary waveforms for the twotransmit channels, red and infrared LEDs, from which the ambient-lightsignal has been subtracted. In addition, FIG. 13 shows an exemplarydifferential signal in a magnified form.

For further signal processing, a block formation for the individualsignals initially occurs. For this purpose, the signals are divided upinto blocks of equal lengths, the individual blocks overlapping. FIG. 14illustrates the block formation for further signal processing. Blocks ofa length of l_(B) are formed from the samples of a useful signal, a newblock being formed every l_(a) samples.

The useful signals are subsequently fed to a frequency-separating means.It is the task of the frequency-separating means to filter the directcomponent and the pulsatile portion from the input signals. In theimplementation of the inventive embodiment, the separating frequency ofthe frequency-separating means amounts to about 0.5 Hz. FIG. 15 a showsthe exemplary curve of an input signal being fed to thefrequency-separating means. In addition, FIG. 15 a depicts the low-passfiltered portion (DC portion) of the input signal. FIG. 15 b) depictsthe associated high-pass portion (AC portion) of the input signal.Further signal processing only relates to the high-pass portion of theinput signal.

The high-pass filtered useful signals are now fed to an adaptive filter330. It is the task of the filter, also referred to as interferencecanceller, to reduce interferences which were present in thetransmission band and were mirrored, after demodulation, into the usefulband in an attenuated state, cf. FIG. 9 d). The differential signalwhich contains the frequencies of the interference in the useful bandhas been formed by subtraction from the dark transmit channels. Thedifferential signal differs in phase and amplitude from theinterferences overlaid on the useful signals. The phase difference iscaused by the sampling offset in time, the difference in amplitude iscaused both by the sampling which is offset in time, and by thesubtraction. It is therefore the task of the adaptive filter to filterout the undesired image frequencies from the useful signals using thedifferential signal. For this purpose, an interfering signal isconstructed, from the differential signal, which is as close as possibleto the interference overlaid upon the useful signal. There are severalmathematical methods of determining the coefficients for adaptive filter330. One known method would be to select the coefficients of adaptivefilter 330 such that the deviation between the differential signal andthe useful signal is minimized. For determining the coefficients, thecomplex total least squares fit method is also to be mentioned here.

FIG. 16 shows the model of the adaptive filter with the time-discreteinput quantities {right arrow over (w)}^(A) _(r) and {right arrow over(w)}A_(i) for the two input signals of the bright transmit channels forred and infrared, A indicating that the input signals are high-passfiltered. In principle, the operations described below are applied toboth input quantities separately, since the interference contemplated ispresent in them in a phase-shifted manner. The differential signal isalso high-pass filtered as a matrix W_(c) ^(A), and forms the basis fordetermining the adaptive filter coefficients {right arrow over (λ)}_(r)and {right arrow over (λ)}_(i). Matrix W_(c) ^(A) results from blocks ofthe differential signal which are high-pass filtered to remove thedirect component. The columns of the matrix each form a block ofsamples, e.g. of a length of 256. This block is indented in the matrixon a column-by-column basis, by one sample each, the matrix has as manycolumns as there are coefficients for the adaptive filter. The matrixmay be described as[W _(c) ^(A)]_(ij)(k)=w _(c) ^(A)(i+k·l _(a) +j)∀jε{0, 1, . . . , N _(ifc)}∀iε{0, 1, . . . , l _(B)−1}  (1)wherein w_(c) ^(A) represents the high-pass filtered elements of thedifferential signal, k is a discrete control variable of the blockformation, l_(a) is the jump constant in the block formation, l_(B) isthe block length, and N_(ifc) is the filter arrangement, i.e. the numberof filter coefficients of the adaptive filter, or interferencecanceller, reduced by one. The output of the adaptive filter thus is aweighted sum of blocks of the differential signals, the blocks havingbeen shifted by one sample each. Using the adaptive filter, theinterference vectors are initially reconstructed, which are designatedby {right arrow over (w)}^(s) _(r) and {right arrow over (w)}^(S) _(i)in FIG. 16 and overlaid on input signals {right arrow over (w)}^(A) _(r)and {right arrow over (w)}^(A) _(i). By means of subtraction, theinterference effects in the input signals {right arrow over (w)}^(A)_(r) and {right arrow over (w)}^(A) _(i) are reduced, as is depicted inFIG. 16.

What is initially sought for is a linear combination {right arrow over(λ)} of basis W_(c) ^(A) which best reproduces the input signal, i.e. areconstruction of the interference has been overlaid on an input signal{right arrow over (w)}^(A).{right arrow over (w)} ^(A) =W _(c) ^(A){right arrow over (λ)}  (2)

There are more equations than unknown variables, in that one assumesthat the adaptive filter comprises fewer coefficients than the blocklength to be processed. This is why there is no specific solution inthis case. What is sought for is a vector {right arrow over (λ)} whichbest fits the over-determined equation system:∥W _(c) ^(A){right arrow over (λ)}−{right arrow over (w)}^(A)∥→Minimum  (3)

This problem may be addressed using the pseudo inverse. Thus, usingvector {right arrow over (λ)}, one obtains a linear combination of W_(c)^(A) which may be used to describe the interference.(W _(c) ^(A))^(#) {right arrow over (w)} ^(A)={right arrow over(λ)}  (4)

Thus, the interferer may be reconstructed on the basis of the inputsignal:{right arrow over (w)} ^(s) =W _(c) ^(A)(W _(c) ^(A))^(#) {right arrowover (w)} ^(A)  (5)

It may also be seen from FIG. 16 that the difference between theestimated interferer and the input signal results in the filteredsignal:{right arrow over (y)} ^(A) ={right arrow over (w)} ^(A) −{right arrowover (w)} ^(s)  (6)or{right arrow over (y)}={right arrow over (w)} ^(A) −W _(c) ^(A)(W _(c)^(A))^(#) {right arrow over (w)} ^(A)(E−W _(c) ^(A)(W _(c)^(A))^(#))  (7)wherein E represents an identity matrix. An alternative implementationof the present invention would be a filter which implements a notchfilter on the basis of the knowledge of the frequencies occurring in thedifferential signal, which is switched into the path of the usefulsignal, and which attenuates the frequencies of the differential signal.

Since examinations are subsequently performed in the frequency range,the input signals are transformed into the frequency range by means ofFourier transformation. Due to the block formation, unwanted sideeffects result in the frequency range. A block formation is to beequated with a multiplication of a rectangular pulse, which masks outthe very block under consideration from a receive signal, by the receivesignal itself. If this block is subject to Fourier transformation, onewill obtain, in the frequency range, a convolution of theFourier-transformed rectangular pulse (since function) with the actualspectrum of the sequence of receive signal samples. To reduce theunfavorable effects caused by the convolution with the sinc function inthe frequency range, the block of receive signal samples is multiplied,in the time domain, by a window function having a narrower spectrum thanthe sinc function. For implementing the embodiment, a Kaiser-Besselfunction is used for this purpose. FIG. 17 depicts the waveform of aKaiser-Bessel window by way of example. Multiplication of the signalblocks by the window function may optionally also be performed prior tothe adaptive filtering.

For further signal processing, the two useful signals are nownormalized. Subsequently, the Fourier transformation is conducted. Afterthe Fourier transformation, the spectra may be presented in differentviews, such as their curve as a function of time or as a function of thefrequency. FIG. 18 shows exemplary spectra of the normalized signalsfrom the bright transmit channels red and infrared. The spectra showsignals under good conditions, i.e. with relatively little interference.The Fourier transformation 335 is followed, in a next signal processingstep, by applying a spectral mask 340 for determining the heart rate.The Fourier transformation of the two signals from the bright transmitchannels initially provides two spectra. If the two signals wereundisturbed, it would be possible to represent one of the two spectra asa linear combination of the other, respectively. However, since the twospectra comprise interferences, it is initially not possible to mergethem into each other by a linear combination.

In FIG. 19, the two spectra for respectively identical frequency valuesare plotted against one another. One may see that the dots do not lie ona straight line, which would indicate a linear relationship between thetwo spectra. If the two spectra did not comprise any interferences, anoriginal straight line would result with this representation. To solvethis problem, an original straight line is now sought for using themethod of the least squares fit, the sum of the square distances of alldots from this original straight line being minimized. This method isknown by the synonym of the total least squares fit method.

FIG. 20 a) and FIG. 20 b) are to illustrate the approach in the totalleast squares fit method. Unlike the least squares fit method, which isdepicted in FIG. 20 a), in the total least squares fit method the actualdistance of a dot from a straight line is minimized, cf. FIG. 20 b).This approach initially leads to an over-determined equation system. Theover-determined equation system may be solved using a singular valuedecomposition so as to find a solution which corresponds to the totalleast squares fit method. Using the singular value decomposition,initially the matrix representing the over-determined linear equationsystem is decomposed. This results in a matrix containing, on itsdiagonal, the singular values of the equation system. By maintaining themaximum singular value, and by setting all other singular values tozero, this matrix is reduced to rank 1, and the problem is thus tracedback to a solvable linear equation system. Such a straight solution lineis drawn in FIG. 19; it is located halfway between two other straightlines defining the range of values of valid slopes which result from thereference measurements of the SpO2 values. The slope of this straightline now represents a measure of the blood oxygen saturation of thesubject. A reference spectrum may now be determined from the linearequation system which has been determined using the singular valuedecomposition.

The slope of the original straight line which has been determined inthis manner may initially be distorted if a high-amplitude interferenceidentically overlays in the two spectra. To reduce this type ofinterference, the spectral mask is employed. The function of thespectral mask 340 may be described as follows. In principle, it is aspectral method which browses the Fourier coefficients of the pulsesignal within the spectrum so as to set all coefficients which do notbelong to the pulse signal to zero. The principle of the spectral maskis based on the fact that the frequency components of the pulse wavediffer from those of other interferers. The algorithm of the spectralmask fundamentally is a binary mask comprising the elements {0, 1}, bywhich the spectrum is multiplied on a point-by-point basis so as tosuppress those Fourier coefficients which do not belong to the pulsesignal.

FIG. 21 a) shows the exemplary curve of the quotient of two spectra ofthe waveforms of the bright transmit channels, FIG. 21 b) shows, in thiscontext, the curve of a reference spectrum which has been corrected withregard to interferences. Both spectral curves are plotted at fourdifferent points in time, respectively, k2=1 . . . 4. If the quotient ofthe two spectra of FIG. 21 a) is compared to the reference spectrumacross several time windows, it becomes clear that the quotient iscorrect only above the frequency components of the pulse signal, and isthe same for all of these frequencies. Problem arise when the amplitudesof the interferences become larger than those of the pulse wave.

By way of example, FIG. 22 a shows a spectrum of a signals disturbed byinterfering signals, the amplitudes of which are larger than theamplitudes of the actual pulse wave. The quotient of two spectra isundefined at the frequencies of an interferer, and it bears no relationto the blood oxygen saturation of a subject. Without the spectral mask,dominant features would lead to an incorrect blood oxygen saturationvalue, as is shown in FIG. 22. Studies have shown that such dominantinterferences mostly occur within both spectra, i.e. within the spectrumof the red signal as well as within the spectrum of the infrared signal.This results in that, in the quotient formation, quotients of a value of1 arise. A quotient of a value of 1 corresponds to a blood oxygensaturation value of approx. 80%. It is now the task of the spectral maskto differentiate the frequency components of the pulse wave from thoseof the interferers.

The spectral mask exhibits an algorithm of the harmonic relation. Themethod of the harmonic relation is based on findings of examiningnumerous pulse signals for their spectral properties. The fundamentalfinding is the harmonic relation of the three relevant frequencies f_(g)of the fundamental wave, f_(o1) and f_(o2) of the second harmonic. Inthis context, it is also known that the second harmonic is at double thefrequency of the fundamental wave, and that the third harmonic is atthree times the frequency of the fundamental wave. On the basis of thisrelation, a mask may now be created which masks in, in the frequencyrange, those frequency portions of double and three times the frequencyof a fundamental wave, i.e. exhibits a 1 at these locations, and masksout all other frequencies, i.e. has a 0 at these locations. A sum maythen be formed from the remaining coefficients, the sum being associatedwith the fundamental frequency. This process may then be repeated forany potential heart rates feasible, for example within a range from30-300 Hz, and subsequently, that frequency at which the sum ismaximized may be selected. A further property which may be taken intoaccount in this context is that the amplitudes of the respectiveharmonics exhibit a decaying characteristic. This means that at thefirst harmonic or at double the frequency of the fundamental wave, theamplitude has a smaller amplitude than the fundamental wave itself. Atthe second harmonic, which has three times the frequency of thefundamental wave, the amplitude is smaller, in turn, than at the firstharmonic. Values for which the appropriate condition of the decayingspectrum is not met will not be considered in the search for themaximum.

Now the heart rate may be determined via the position of the spectralmask. In the realization of the inventive embodiment of FIG. 3, theheart rate will be output at output 345.

After multiplication by the spectral mask, only the relevant frequencycomponents were detected. According to the same principle as was alreadydescribed, a quotient of the relevant spectra may now be determinedagain using the complex total least squares fit method and singularvalue decomposition. In this context, only those frequency componentsare used which have been determined by means of the spectral mask. Viathese interference-corrected spectra, the original straight line and itsslope may now be determined. In addition to the slope of the originalstraight line, it is also possible to extract a measure of thereliability of the slope determined from the matrix decomposition of theover-determined linear equation system. The variance in accordance withthe Frobenius norm, which may be directly obtained from the matrixdecomposition, indicates the similarity of the two signals.

The variance is used as an indictor of excessive interference effectswhich prevents the computation of the physiological parameters withinthe specified tolerance range. Then this variance can be output atoutput 355 in accordance with FIG. 3. The complex total least squaresfit method has a calibration function 360 connected downstream from it.The slope of the original straight line which has been determined usingthe complex total least squares fit method and which is representativeof the blood saturation value of the subject is passed on to acalibration function 360. The calibration function directly associatesSpO₂ values (blood saturations values) with the slope values obtained.The respective SpO₂ values are then output, in accordance with FIG. 3,at output 365. FIG. 23 shows an exemplary characteristic curve of acalibration function. It can be seen how blood saturation values (SpO₂values) are associated with quotients (ratio). The characteristic curvesof the calibration function are empirically determined using referencemeasurements.

One advantage of the present invention is that adaptive filtering, whichis specifically tailored to the field of application of plethysmographyand pulse oximetry, and the combination of the specifically adaptedadaptive filtering significantly improve the reliability of theplethysmograms and enable effective filtering of ambient-lightinterferences and interferences caused by electromagnetic fields (e.g.high-frequency surgery).

Another advantage is that using singular value decomposition forcalculating SpO₂ values from the complex spectra, a measure ofreliability in the form of a variance may be extracted and used forassessing the quality of the result, or that a malfunction may bereliably detected.

An additional advantage is that using the inventive apparatus formeasuring the blood oxygen saturation and heart rate, reliablemeasurements may be made even at a low arterial blood volume pulsationwhile the patient is moving, which is due to the additional level ofreliability obtained by the adaptive filtering.

In general terms, one may state that the quality of treatment for apatient, in particular in intensive care and in operating rooms, may beconsiderably improved by the present invention. Due to the increasedreliability and robustness of the method, diagnostic errors due todistorted measurements and/or due to unreliable measurement values canbe considerably reduced.

While this invention has been described in terms of several embodiments,there are alterations, permutations, and equivalents which fall withinthe scope of this invention. It should also be noted that there are manyalternative ways of implementing the methods and compositions of thepresent invention. It is therefore intended that the following appendedclaims be interpreted as including all such alterations, permutationsand equivalents as fall within the true spirit and scope of the presentinvention.

The invention claimed is:
 1. An apparatus for reducing an interferenceportion in a time-discrete signal further comprising a useful portion,the apparatus comprising: a first provider for providing thetime-discrete signal comprising the interference portion and the usefulportion, the first provider being adapted to sample an iterative opticalsignal which corresponds to bright periods during which a transmit lightsource adopts an on state; a second provider for providing a firsttime-discrete reference signal comprising a first frequency component ofthe interference portion, and a second time-discrete reference signalcomprising a second frequency component of the interference portion, thefirst and second frequency components being shifted in phase, and thesecond provider for providing the first and second reference signalsbeing adapted to sample two optical signals which correspond to darkperiods during which no transmit light source adopts an on state; asubtractor for generating a differential signal from the two referencesignals, the differential signal comprising a third frequency componentcaused by the first and second frequency components; and a manipulatorfor manipulating the time-discrete signal on the basis of thedifferential signal, such that in a manipulated time-discrete signal theinterference portion is reduced.
 2. The apparatus as claimed in claim 1,wherein the first provider for providing the time-discrete signal andthe second provider for providing the first and second time-discretereference signals are implemented to provide the time-discrete signalsby sampling analog signals using a sampler comprising a samplingfrequency.
 3. The apparatus as claimed in claim 2, wherein the sampleris implemented to generate the time-discrete signal, the first andsecond time-discrete reference signals in that sampling is sequentiallyperformed at different points in time at regular time intervals.
 4. Theapparatus as claimed in claim 3, wherein the first provider forproviding the time-discrete signal and the second provider for providingthe first and second time-discrete reference signals each comprise a lowpass whose cutoff frequency corresponds to at least the reciprocal valueof half the sampling duration of the sampler.
 5. The apparatus asclaimed in claim 4, wherein the manipulator for manipulating thetime-discrete signal is adapted to manipulate frequency components inthe differential signal in terms of their amplitudes and phase positionssuch that a difference between the differential signal and thetime-discrete signal is reduced.
 6. The apparatus as claimed in claim 5,wherein the manipulator is implemented to filter the differential signalusing a digital filter, the coefficients of the digital filter being setsuch that the difference between the time-discrete signal and thefiltered differential signal is smaller than the difference between thetime-discrete signal and the differential signal.
 7. The apparatus asclaimed in claim 4, wherein the manipulator is adapted to filter thetime-discrete signal using a digital filter and to set the coefficientsof the digital filter such that frequency components in thetime-discrete signal which come up in the differential signal arereduced in terms of their amplitudes.
 8. The apparatus as claimed inclaim 1, wherein the manipulated time-discrete signal is supplied to aprocessor implemented to determine a straight regression line in a largegroup of dots using the CTLSF method (complex total least squares fit)by means of a singular value decomposition.
 9. The apparatus as claimedin claim 8, wherein the processor is implemented to determine the linearcoefficient using the CTLSF method (complex total least squares fit) fortwo linearly dependent spectra comprising independent interferences. 10.The apparatus as claimed in claim 9, wherein the processor isimplemented to determine the linear coefficient using a singular valuedecomposition.
 11. The apparatus as claimed in claim 8, wherein theprocessor is implemented to determine the reliability measure from thesingular values of a matrix composed of two spectra of two brighttransmit channels, a spectrum of the bright transmit channelrepresenting a column of the matrix.
 12. The apparatus as claimed inclaim 11, wherein the processor is to adapted to derive the reliabilitymeasure from the Frobenius norm of the matrix.
 13. The apparatus asclaimed in claim 1, implemented to determine heart rate signals using aspectral analysis of bright transmit channels.
 14. The apparatus asclaimed in claim 13, implemented to determine a spectral mask whichinsulates, in the frequency range, those signal portions from thespectrum which comprise the same spectral characteristic as a signalsought for.
 15. The apparatus as claimed in claim 14, implemented todetermine a spectral mask for pulse signals of a living being withregard to a potential fundamental wave frequency and potential harmonicfrequencies, as well as their relations to each other, from the spectraof the bright transmit channels.
 16. The apparatus as claimed in claim15, implemented to infer a subject's heart rate from the relation offundamental wave components and harmonic components within the spectrumof the bright transmit channels.
 17. The apparatus as claimed in claim1, wherein the processor is implemented to output a reliability measureof a physiological parameter determined.
 18. The apparatus as claimed inclaim 17, wherein the processor is implemented to determine a varianceof the difference between two bright transmit channels or their spectraand to derive the reliability measure therefrom.
 19. The apparatus asclaimed in claim 17, wherein the processor is implemented to determine avariance from the difference between bright transmit channels comprisingreduced interference, or their spectra, and to derive a reliabilitymeasure therefrom.
 20. The apparatus as claimed in claim 1, wherein thefirst provider for providing the time-discrete signal and the secondprovider for providing the first and second time-discrete referencesignals are implemented to receive, to store or to generate a binarycode word comprising a length and indicating the arrangement of thebright and dark periods, and to link the binary code word with anoriginal signal in a block-by-block manner so as to acquire a digitalsignal of a transmit channel, the transmit channel being determined bythe binary code word, and the block length being defined by the lengthof the code word, and a value of the transmit channel being extractedper block-by-block linking.
 21. The apparatus as claimed in claim 20,wherein the first provider for providing the time-discrete signal andthe second provider for providing the first and second time-discretereference signals are implemented to form a scalar product between thebinary code word and a block of the original signal of the length of thebinary code word, to weight the result, to link it with other resultsand to associate an overall result with a transmit channel.
 22. Theapparatus as claimed in claim 1, wherein the manipulator formanipulating the time-discrete signal is implemented to form columns ofa matrix from the differential signal in a block-by-block manner, toregard these as coefficients of a linear over-determined equationsystem, and to solve same by an optimization criterion, as well as toadaptively track the coefficients.
 23. The apparatus as claimed in claim22, implemented to utilize, for spectral analysis, only such frequencyportions of a spectrum which are relevant to a pulse portion.
 24. Theapparatus as claimed in claim 1, wherein the first provider forproviding the time-discrete signal and the second provider for providingthe time-discrete reference signals are adapted to sample opticalsignals.
 25. The apparatus as claimed in claim 1, further comprising aformer for forming a weighted sum of the two time-discrete referencesignals, which supplies the weighted sum of the two time-discretereference signals to the first provider for providing the time-discretesignal, and the first provider for providing the time-discrete signalbeing implemented to subtract the weighted sum from an original signaland to provide the result as a time-discrete signal.
 26. The apparatusas claimed in claim 1, wherein the first provider for providing thetime-discrete signal is implemented to provide the signal on the basisof an infrared transmit light source or a red transmit light source. 27.The apparatus as claimed in claim 1, wherein the first provider forproviding a time-discrete signal is implemented to provide a signalwhich has passed a tissue of a living being.
 28. The apparatus asclaimed in claim 1, wherein the apparatus for reducing an interferenceportion in a time-discrete signal is implemented to provide a signalcomprising information on a physiological parameter.
 29. The apparatusas claimed in claim 1, wherein the apparatus for reducing aninterference portion in a time-discrete signal is implemented to providea signal comprising information on a heart rate or a blood oxygensaturation value of a living being.
 30. The apparatus as claimed inclaim 1, wherein the first provider for providing a time-discrete signalis implemented to process an iterative optical signal, the opticalsignal comprising sequences, and a sequence comprising at least twobright periods during which a transmit light source adopts an ON stateand at least one dark period during which no transmit light sourceadopts the ON state, and the at least two bright periods beingirregularly arranged within a sequence, and the first provider forproviding the time-discrete signal further being implemented to providethe time-discrete signal in accordance with a bright transmit channel onthe basis of the information on the arrangement of the bright periodswithin the sequence.
 31. The apparatus as claimed in claim 1, whereinthe second provider for providing the first and second time-discretereference signals is implemented to receive iterative optical signals,the optical signal comprising sequences, and a sequence comprising atleast two dark periods during which no transmit light source adopts anON state and at least one bright period during which a transmit lightsource adopts an ON state, and the at least two dark periods beingirregularly arranged within the sequence.
 32. The apparatus as claimedin claim 1, wherein a sequence of an optical signal is based on a clockin accordance with which the bright and dark periods occur.
 33. Theapparatus as claimed in claim 1, wherein the first provider forproviding the time-discrete signal and the second provider for providingthe first and second time-discrete reference signals are implemented tooperate at a clock higher than 800 Hz.
 34. The apparatus as claimed inclaim 1, wherein the sequence of the optical signal comprises at leasttwo further bright periods originating from a second transmit lightsource, the first provider for providing the time-discrete signal beingimplemented to extract a further bright transmit channel using a furtherbinary code word.
 35. The apparatus as claimed in claim 1, wherein thefirst provider for providing the time-discrete signal is implemented tosubdivide the time-discrete signal into blocks, multiply it by a windowfunction, normalize it and/or determine its spectrum.
 36. The apparatusas claimed in claim 1, implemented to determine, from the ratio of twospectral values of two bright transmit channels, blood oxygen saturationor an SpO2 value of an artery which has been radiated.
 37. The apparatusas claimed in claim 1, wherein the processor is implemented to receive,to store or to generate a table which associates blood saturation values(SpO2) with quotients of spectral values.
 38. A method of reducing aninterference portion in a time-discrete signal further comprising auseful portion, the method comprising: providing a time-discrete signalcomprising the interference portion and the useful portion, comprisingsampling an iterative optical signal which corresponds to bright periodsduring which a transmit light source adopts an on state; providing afirst time-discrete reference signal comprising a first frequencycomponent of the interference portion; providing a second time-discretereference signal comprising a second frequency component of theinterference portion, the first and second frequency components beingshifted in phase, and providing the first and second reference signalscomprising sampling optical signals which correspond to dark periodsduring which no transmit light source adopts an on state; subtractingthe two reference signals and providing a differential signal comprisinga third frequency component caused by the first and second frequencycomponents; and manipulating the time-discrete signal on the basis ofthe differential signal such that in a manipulated time-discrete signalthe interference portion is reduced.